Abstract
Research in clinical psychology, since its inception, has been aimed at analyzing, predicting and explaining the effect of treatments, by studying the change of patients in the course of them. To study the effects of therapy, research based on quantitative analysis models has historically used classical methods of parametric statistics, such as Pearson correlations, least squares regressions Student’s T-Tests and Variance Analysis (ANOVA). Hierarchical linear models (HLMs) represent a fundamental statistical strategy for research in psychotherapy, as they allow to overcome dependence on the observations usually presented in your data. The objective of this work is to present a guide to understanding, applying and reporting HLMs to study the effects of psychotherapy.
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References
Bates, D., Mäechler, M., Bolker, B., Walker, S.: Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67(1), 1–48 (2015). https://doi.org/10.18637/jss.v067.i01
Behn, A.J., Errázuriz, P.A., Cottin, M., Fischer, C.: Change in symptomatic burden and life satisfaction during short-term psychotherapy: focusing on the role of family income. Counselling Psychother. Res. 18(2), 133–142 (2017). https://doi.org/10.1002/capr.12158
Gómez Penedo, J.M., Constantino, M.J., Coyne, A., Westra, H., Antony, M.: Markers for context-responsiveness: client baseline interpersonal problems moderate the efficacy of two psychotherapies for generalized anxiety disorder. J. Consult. Clin. Psychol. 85(10), 1000–1011 (2017). https://doi.org/10.1037/ccp0000233
Gómez Penedo, J.M., Juan, S., Manubens, R.T., Roussos, A.: The study of change in psychotherapy: conceptual challenges and problems of empirical research. Yearbook Psychol. Res. 24, 15–24 (2018)
Hayes, A.F.: Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. Guilford Publications, New York (2017)
Bucci, N., et al.: Factor analysis of the psychosocial risk assessment instrument. In: Tan, Y., Shi, Y., Tang, Q. (eds.) DMBD 2018. LNCS, vol. 10943, pp. 149–158. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93803-5_14
Gaitán-Angulo, M., Viloria, A., Abril, J.E.S.: Hierarchical ascending classification: an application to contraband apprehensions in colombia (2015–2016). In: Tan, Y., Shi, Y., Tang, Q. (eds.) DMBD 2018. LNCS, vol. 10943, pp. 168–178. Springer, Heidelberg (2018). https://doi.org/10.1007/978-3-319-93803-5_16
Viloria, A., Lezama, O.B.P.: An intelligent approach for the design and development of a personalized system of knowledge representation. Procedia Comput. Sci. 151, 1225–1230 (2019)
Viloria, A., Lis-Gutiérrez, J.P., Gaitán-Angulo, M., Godoy, A.R.M., Moreno, G.C., Kamatkar, S.J.: Methodology for the design of a student pattern recognition tool to facilitate the teaching - learning process through knowledge data discovery (big data). In: Tan, Y., Shi, Y., Tang, Q. (eds.) DMBD 2018. LNCS, vol. 10943, pp. 670–679. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93803-5_63
Viloria, A., et al.: Determination of dimensionality of the psychosocial risk assessment of internal, individual, double presence and external factors in work environments. In: Tan, Y., Shi, Y., Tang, Q. (eds.) DMBD 2018. LNCS, vol. 10943, pp. 304–313. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93803-5_29
Wang, J., Xie, H., Fisher, J.H.: Multilevel Models: Applications Using SAS. De Gruyter, Berlin (2012)
Areas, M., Roussos, A., Hirsch, H., Hirsch, P., Becerra, P., Gómez Penedo, J.M.: Evaluation of a research device oriented to practice in the development of a feedback system in psychotherapy. Argentine J. Psychol. Clinic 27(2), 229–249 (2018)
Westra, H.A., Constantino, M.J., Antony, M.M.: Integrating motivational interviewing with cognitive-behavioral therapy for severe generalized anxiety disorder: an allegiance controlled randomized clinical trial. J. Consult. Clin. Psychol. 84(9), 768–782 (2016). https://doi.org/10.1037/ccp0000098
Zilcha-Mano, S., Errázuriz, P.: One size does not fit all: examining heterogeneity and identifying moderators of the alliance–outcome association. J. Counseling Psychol. 62(4), 579–591 (2015). https://doi.org/10.1037/cou0000103
Hox, J., Maas, C.: Multilevel analysis. In: Encyclopedia of Social Measurement, vol. 2, pp. 785–793 (2005). https://doi.org/10.1016/b0-12-369398-5/00560-0
Mellado, A., et al.: Disentangling the change-alliance relationship: observational assessment of the therapeutic alliance during change and stuck episodes. Psychotherapy Res. 27(5), 595–607 (2017). https://doi.org/10.1080/10503307.2016.1147657
Ogles, B.M.: Measuring change in psychotherapy research. In: Lambert, M.J. (ed.) Bergin and Garfields’s Handbook of Psychotherapy and Behavior Change, pp. 134–166. Wiley, New Jersey (2013)
Raudenbush, S.W., Bryk, A.S.: Hierarchical Linear Models: Applications and Data Analysis Methods, 2nd edn. Sage, Thousand Oaks (2002)
Raudenbush, S.W., Bryk, A.S., Cheong, Y.F., Congdon, R.T., du Toit, M.: HLM7: Hierarchical Linear and Nonlinear Modeling. Scientific Software International, Chicago (2011)
Skrondal, A., Rabe-Hesketh, S.: Generalized Latent Variable Modeling. Chapman & Hall/CRC, Boca Raton (2004)
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Silva, J. et al. (2019). Educational Psychology in Latin America: With Linear Hierarchical Models. In: Wang, G., El Saddik, A., Lai, X., Martinez Perez, G., Choo, KK. (eds) Smart City and Informatization. iSCI 2019. Communications in Computer and Information Science, vol 1122. Springer, Singapore. https://doi.org/10.1007/978-981-15-1301-5_19
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